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在面向移动单元的遥感影像服务中,受信息分发信道窄等因素影响,高价值目标信息根据价值权重进行自适应压缩的方法将发挥重大作用。本文设计了一套面向移动服务的遥感影像感兴趣区全流程自动提取压缩重构方法,利用数学形态学进行了边缘检测,获取了边缘点数量,确定了感兴趣区域,生成了感兴趣区掩模,并将小波域上的感兴趣区系数进行了提升,对小波系数矩阵进行了SPIHT量化编码和解码重构。通过试验,模拟在有限的传输带宽下,自动提取感兴趣区,对感兴趣区进行优先编码并重构全自动流程,使得移动端获得高价值目标信息优于背景信息的重构效果,且具有较高的压缩比,该方法将促进遥感影像在移动服务中的普及应用。
In remote sensing image services for mobile units, the method of adaptively compressing high-value target information according to the value weight will play an important role due to the narrow channel of information distribution and other factors. In this paper, we design a full-process automatic extraction compression and reconstruction method for ROI-based region of interest for mobile services. Edge detection is performed by using mathematical morphology. The number of edge points is obtained, the ROIs are identified, and ROIs are generated The coefficients of the region of interest in the wavelet domain are improved. The SPIHT quantization coding and decoding reconstruction are carried out on the wavelet coefficient matrix. Through experiments, we can simulate the region of interest extracted automatically with limited transmission bandwidth, preferentially code the region of interest and reconstruct the fully automated process, so that the mobile end can obtain the reconstruction effect that the high-value target information is better than the background information, High compression ratio, this method will promote the remote sensing image in the mobile service popularization and application.